A generalized ordered logit analysis of risk factors associated with driver injury severity

• Published in: Journal of public health Vol. 29; no. 2; pp. 471 - 477
• Main Authors: Aidoo, Eric Nimako, Ackaah, Williams
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2021; Springer Nature B.V
• Subjects: Crashes; Driver behavior; Epidemiology; Health Promotion and Disease Prevention; Injury analysis; Medicine; Medicine & Public Health; Occupant injuries; Original Article; Public Health; Risk analysis; Risk factors; Traffic accidents; Accra; Ordered response; Driver injury severity; Generalized ordered logit model
• ISSN: 2198-1833; 1613-2238
• DOI: 10.1007/s10389-019-01135-8

Aim Road traffic crashes remain a major public health issue and have been the subject of debate in many studies due to their effect on society. This study contributes to the discussion by investigating the risk factors that significantly contribute to driver injury severity sustained in traffic crashes. Subject and methods Using the crash data from the Greater Accra region of Ghana, spanning a 3-year period (2014–2016), a generalized ordered logit (GOL) model was estimated to determine the effect of a wide range of variables on driver injury severity outcome. Results The results suggest that, in the event of a crash, more severe driver injury was influenced by multiple factors including driver’s gender, driver’s action (e.g., turning, overtaking, going ahead), number of vehicles involved, day of week of the crash, vehicle size, and road width. Conclusion The findings of this study highlight the need to further study risk factors significantly influencing driver injury severity.